Triple

T636773
Position Surface form Disambiguated ID Type / Status
Subject Citroën E16638 entity
Predicate sportsAchievement P17391 FINISHED
Object multiple WRC manufacturers' titles LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: multiple WRC manufacturers' titles | Statement: [Citroën, sportsAchievement, multiple WRC manufacturers' titles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: sportsAchievement
Context triple: [Citroën, sportsAchievement, multiple WRC manufacturers' titles]
  • A. sportsCareer
    Indicates a relationship where an entity’s professional involvement, roles, or achievements in sports are associated with a particular sport, team, period, or competitive level.
  • B. sportFocus
    Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
  • C. sport
    Indicates that an entity participates in, is associated with, or is characterized by a particular athletic activity or game.
  • D. notableAthlete
    Indicates that the subject is a well-known or distinguished athlete associated with the object (such as a sport, team, or organization).
  • E. popularSport
    Indicates that a sport is widely liked, followed, or played by many people within a certain group or region.
  • F. None of above. chosen

Provenance (4 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4936be1c88190af56540324b57da7 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ee7fdbc8190858e42bb1bfdb3ff completed March 1, 2026, 8:17 p.m.
PD Predicate disambiguation batch_69a49d0483908190a5ec42a7403c258e completed March 1, 2026, 8:09 p.m.
PDg Predicate description generation batch_69a49defe58c8190bd39ef47c9f660a7 completed March 1, 2026, 8:13 p.m.
Created at: March 1, 2026, 7:35 p.m.